Physical Oceanography

In ECCO_standard_plots.jl (➭ code link) we visualize a selection of climate-relevant variables and indices as an example. These were derived from gridded estimates of the ocean state for physical variables like temperature, salinity, and currents (see examples/ECCO_standard_analysis.jl) and archived using zenodo.org (see OceanStateEstimation.ECCOdiags_download, and OceanStateEstimation.ECCOdiags_add).

The underlying gridded fields can in turn be retrieved from ecco-group.org and, for the ECCOv4r2 estimate, from Harvard Dataverse. Two monthly climatologies (ECCOv4r2 and OCCA) are also readily available using the Julia artifact system as explained below. These can be relatively large files, compared to the package codes, so they are handled lazily (only downloaded when needed).

Basic Usage

using OceanStateEstimation
get_occa_variable_if_needed("SIarea")
readdir(OCCAclim_path)

or

using OceanStateEstimation, MeshArrays
γ=GridSpec("LatLonCap",MeshArrays.GRID_LLC90)
tmp=OceanStateEstimation.get_ecco_files(γ,"ETAN")

Bio-Geo-Chemical Climatology

CBIOMES-global (alpha version) is a global ocean state estimate that covers the period from 1992 to 2011. It is based on Forget et al 2015 for ocean physics MIT general circulation model and on Dutkiewicz et al 2015 for marine biogeochemistry and ecosystems Darwin Project model.

• CBIOMES_climatology_plot (➭ code link) : visualize the climatology maps interactively using Pluto.jl
• CBIOMES_climatology_create (➭ code link) : recreate the climatology file. The original is archived here in zenodo.

Or in the julia REPL, for example :

using OceanStateEstimation, NCTiles
OceanStateEstimation.CBIOMESclim_download()
fil_out=joinpath(CBIOMESclim_path,"CBIOMES-global-alpha-climatology.nc")
nc=NCTiles.NCDataset(fil_out,"r")

References

• OCCA : Forget 2010
• ECCO v4 : Forget et al 2015
• CBIOMES-global : Forget 2018